This function will iterate on each embedding in embedding_file and
assign the pretrained vector to the associated word in vocabulary_file
if found. Otherwise, the embedding is ignored.

If case_insensitive_embeddings is True, word embeddings are assumed
to be trained on lowercase data. In that case, word alignments are case
insensitive meaning the pretrained word embedding for “the” will be assigned
to “the”, “The”, “THE”, or any other case variants included in
vocabulary_file.

Parameters:

embedding_file – Path the embedding file. Entries will be matched against
vocabulary_file.

vocabulary_file – The vocabulary file containing one word per line.

num_oov_buckets – The number of additional unknown tokens.

with_header – True if the embedding file starts with a header line like
in GloVe embedding files.

case_insensitive_embeddings – True if embeddings are trained on lowercase
data.

Returns:

A Numpy array of shape [vocabulary_size+num_oov_buckets,embedding_size].